Data anonymization of blockchain-based processing pipeline

ABSTRACT

An example operation may include one or more of anonymizing, via an anonymization service hosted within a trusted execution environment (TEE), raw data provided by a computing node to generate anonymized data, generating, via the anonymization service, an authenticator object that binds together a hash of the raw data and a hash of the anonymized data, transmitting the generated anonymized data to the computing node, and submitting the authenticator object to a blockchain ledger via a blockchain transaction.

BACKGROUND

A centralized platform stores and maintains data in a single location.This location is often a central computer, for example, a cloudcomputing environment, a web server, a mainframe computer, or the like.Information stored on a centralized platform is typically accessiblefrom multiple different points. Multiple users or client workstationscan work simultaneously on the centralized platform, for example, basedon a client/server configuration. A centralized platform is easy tomanage, maintain, and control, especially for purposes of securitybecause of its single location. Within a centralized platform, dataredundancy is minimized as a single storing place of all data alsoimplies that a given set of data only has one primary record.

SUMMARY

One example embodiment provides an apparatus that includes a processorthat is configured to one or more of anonymize, via an anonymizationservice hosted within a trusted execution environment (TEE), raw dataprovided by a computing node to generate anonymized data, generate, viathe anonymization service, an authenticator object that binds together ahash of the raw data and a hash of the anonymized data, transmit thegenerated anonymized data to the computing node, and submit theauthenticator object to a blockchain ledger via a blockchaintransaction.

Another example embodiment provides a method that includes one or moreof anonymizing, via an anonymization service hosted within a trustedexecution environment (TEE), raw data provided by a computing node togenerate anonymized data, generating, via the anonymization service, anauthenticator object that binds together a hash of the raw data and ahash of the anonymized data, transmitting the generated anonymized datato the computing node, and submitting the authenticator object to ablockchain ledger via a blockchain transaction.

A further example embodiment provides a non-transitory computer-readablemedium comprising instructions, that when read by a processor, cause theprocessor to perform one or more of anonymizing, via an anonymizationservice hosted within a trusted execution environment (TEE), raw dataprovided by a computing node to generate anonymized data, generating,via the anonymization service, an authenticator object that bindstogether a hash of the raw data and a hash of the anonymized data,transmitting the generated anonymized data to the computing node, andsubmitting the authenticator object to a blockchain ledger via ablockchain transaction.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagram illustrating a computing network for anonymizinginput data for a data processing pipeline according to exampleembodiments.

FIG. 1B is a diagram illustrating a network of data owners for traininga model via the data processing pipeline according to exampleembodiments.

FIG. 2A is a diagram illustrating an example blockchain architectureconfiguration, according to example embodiments.

FIG. 2B is a diagram illustrating a blockchain transactional flow amongnodes, according to example embodiments.

FIG. 3A is a diagram illustrating a permissioned network, according toexample embodiments.

FIG. 3B is a diagram illustrating another permissioned network,according to example embodiments.

FIG. 3C is a diagram illustrating a permissionless network, according toexample embodiments.

FIG. 4A is a diagram illustrating a process of generating anauthenticator for authenticating anonymized data according to exampleembodiments.

FIG. 4B is a diagram illustrating a process of validating anonymizeddata based on the authenticator object according to example embodiments.

FIG. 5 is a diagram illustrating a method for authenticating anonymizeddata according to example embodiments.

FIG. 6A is a diagram illustrating an example system configured toperform one or more operations described herein, according to exampleembodiments.

FIG. 6B is a diagram illustrating another example system configured toperform one or more operations described herein, according to exampleembodiments.

FIG. 6C is a diagram illustrating a further example system configured toutilize a smart contract, according to example embodiments.

FIG. 6D is a diagram illustrating yet another example system configuredto utilize a blockchain, according to example embodiments.

FIG. 7A is a diagram illustrating a process of a new block being addedto a distributed ledger, according to example embodiments.

FIG. 7B is a diagram illustrating data contents of a new data block,according to example embodiments.

FIG. 7C is a diagram illustrating a blockchain for digital content,according to example embodiments.

FIG. 7D is a diagram illustrating a block which may represent thestructure of blocks in the blockchain, according to example embodiments.

FIG. 8A is a diagram illustrating an example blockchain which storesmachine learning (artificial intelligence) data, according to exampleembodiments.

FIG. 8B is a diagram illustrating an example quantum-secure blockchain,according to example embodiments.

FIG. 9 is a diagram illustrating an example system that supports one ormore of the example embodiments.

DETAILED DESCRIPTION

It will be readily understood that the instant components, as generallydescribed and illustrated in the figures herein, may be arranged anddesigned in a wide variety of different configurations. Thus, thefollowing detailed description of the embodiments of at least one of amethod, apparatus, non-transitory computer readable medium and system,as represented in the attached figures, is not intended to limit thescope of the application as claimed but is merely representative ofselected embodiments.

The instant features, structures, or characteristics as describedthroughout this specification may be combined or removed in any suitablemanner in one or more embodiments. For example, the usage of the phrases“example embodiments”, “some embodiments”, or other similar language,throughout this specification refers to the fact that a particularfeature, structure, or characteristic described in connection with theembodiment may be included in at least one embodiment. Thus, appearancesof the phrases “example embodiments”, “in some embodiments”, “in otherembodiments”, or other similar language, throughout this specificationdo not necessarily all refer to the same group of embodiments, and thedescribed features, structures, or characteristics may be combined orremoved in any suitable manner in one or more embodiments. Further, inthe diagrams, any connection between elements can permit one-way and/ortwo-way communication even if the depicted connection is a one-way ortwo-way arrow. Also, any device depicted in the drawings can be adifferent device. For example, if a mobile device is shown sendinginformation, a wired device could also be used to send the information.

In addition, while the term “message” may have been used in thedescription of embodiments, the application may be applied to many typesof networks and data. Furthermore, while certain types of connections,messages, and signaling may be depicted in exemplary embodiments, theapplication is not limited to a certain type of connection, message, andsignaling.

Example embodiments provide methods, systems, components, non-transitorycomputer readable media, devices, and/or networks, which are directed toconfidential submission of analytic training data while preservingauthenticity of the anonymized data via a blockchain network.

In one embodiment this application utilizes a decentralized database(such as a blockchain) that is a distributed storage system, whichincludes multiple nodes that communicate with each other. Thedecentralized database includes an append-only immutable data structureresembling a distributed ledger capable of maintaining records betweenmutually untrusted parties. The untrusted parties are referred to hereinas peers or peer nodes. Each peer maintains a copy of the databaserecords and no single peer can modify the database records without aconsensus being reached among the distributed peers. For example, thepeers may execute a consensus protocol to validate blockchain storagetransactions, group the storage transactions into blocks, and build ahash chain over the blocks. This process forms the ledger by orderingthe storage transactions, as is necessary, for consistency. In variousembodiments, a permissioned and/or a permissionless blockchain can beused. In a public or permission-less blockchain, anyone can participatewithout a specific identity. Public blockchains can involve nativecryptocurrency and use consensus based on various protocols such asProof of Work (PoW). On the other hand, a permissioned blockchaindatabase provides secure interactions among a group of entities whichshare a common goal but which do not fully trust one another, such asbusinesses that exchange funds, goods, information, and the like.

This application can utilize a blockchain that operates arbitrary,programmable logic, tailored to a decentralized storage scheme andreferred to as “smart contracts” or “chaincodes.” In some cases,specialized chaincodes may exist for management functions and parameterswhich are referred to as system chaincode. The application can furtherutilize smart contracts that are trusted distributed applications whichleverage tamper-proof properties of the blockchain database and anunderlying agreement between nodes, which is referred to as anendorsement or endorsement policy. Blockchain transactions associatedwith this application can be “endorsed” before being committed to theblockchain while transactions, which are not endorsed, are disregarded.An endorsement policy allows chaincode to specify endorsers for atransaction in the form of a set of peer nodes that are necessary forendorsement. When a client sends the transaction to the peers specifiedin the endorsement policy, the transaction is executed to validate thetransaction. After validation, the transactions enter an ordering phasein which a consensus protocol is used to produce an ordered sequence ofendorsed transactions grouped into blocks.

This application can utilize nodes that are the communication entitiesof the blockchain system. A “node” may perform a logical function in thesense that multiple nodes of different types can run on the samephysical server. Nodes are grouped in trust domains and are associatedwith logical entities that control them in various ways. Nodes mayinclude different types, such as a client or submitting-client nodewhich submits a transaction-invocation to an endorser (e.g., peer), andbroadcasts transaction-proposals to an ordering service (e.g., orderingnode). Another type of node is a peer node which can receive clientsubmitted transactions, commit the transactions and maintain a state anda copy of the ledger of blockchain transactions. Peers can also have therole of an endorser, although it is not a requirement. Anordering-service-node or orderer is a node running the communicationservice for all nodes, and which implements a delivery guarantee, suchas a broadcast to each of the peer nodes in the system when committingtransactions and modifying a world state of the blockchain, which isanother name for the initial blockchain transaction which normallyincludes control and setup information.

This application can utilize a ledger that is a sequenced,tamper-resistant record of all state transitions of a blockchain. Statetransitions may result from chaincode invocations (i.e., transactions)submitted by participating parties (e.g., client nodes, ordering nodes,endorser nodes, peer nodes, etc.). Each participating party (such as apeer node) can maintain a copy of the ledger. A transaction may resultin a set of asset key-value pairs being committed to the ledger as oneor more operands, such as creates, updates, deletes, and the like. Theledger includes a blockchain (also referred to as a chain) which is usedto store an immutable, sequenced record in blocks. The ledger alsoincludes a state database which maintains a current state of theblockchain.

This application can utilize a chain that is a transaction log which isstructured as hash-linked blocks, and each block contains a sequence ofN transactions where N is equal to or greater than one. The block headerincludes a hash of the block's transactions, as well as a hash of theprior block's header. In this way, all transactions on the ledger may besequenced and cryptographically linked together. Accordingly, it is notpossible to tamper with the ledger data without breaking the hash links.A hash of a most recently added blockchain block represents everytransaction on the chain that has come before it, making it possible toensure that all peer nodes are in a consistent and trusted state. Thechain may be stored on a peer node file system (i.e., local, attachedstorage, cloud, etc.), efficiently supporting the append-only nature ofthe blockchain workload.

The current state of the immutable ledger represents the latest valuesfor all keys that are included in the chain transaction log. Since thecurrent state represents the latest key values known to a channel, it issometimes referred to as a world state. Chaincode invocations executetransactions against the current state data of the ledger. To make thesechaincode interactions efficient, the latest values of the keys may bestored in a state database. The state database may be simply an indexedview into the chain's transaction log, it can therefore be regeneratedfrom the chain at any time. The state database may automatically berecovered (or generated if needed) upon peer node startup, and beforetransactions are accepted.

Analytical models, for example, machine learning models, artificialintelligence models, and the like, may be iteratively trained usingnumerous data sets. Typically, the more high quality training data thatis used to train the model, the better the predictive accuracy of themodel. Recently, organizations have begun to collaborate when initiallytraining a model to further enhance the pool of training data.Furthermore, once the model has been established, the model may befurther refined over time through continuous or updated trainingintervals. For example, multiple banks may provide training data to adata processing pipeline which iteratively trains a fraud detectionmodel. Once trained, the fraud detection model may be deployed to bankservers for security and fraud detection.

Many types of training data include sensitive user data, also referredto as personally identifiable information (PII). Local and federalregulations require organizations that house user data including PII toprotect the privacy of the data and prevent the data from exposure tounauthorized parties. Privacy of the data can be problem when training amachine learning model among different/non-trusting organizations. Toaddress the privacy issue, each organization may anonymize the data insome way so as to prevent the data from exposure to the otherorganizations that are participating in the training of the model.However, when the data is anonymous, it prevents the other organizationsfrom verifying the accuracy of the data. For example, a maliciousorganization may submit fake data.

The example embodiments are directed to an anonymization service (AS)that can anonymize training data for an analytic model while alsoenabling such training data to be authenticated/validated should asubsequent request be made. Each organization (e.g., data owner) thatparticipates in the training of the analytic model may include its owninstance of the anonymization service. For example, the anonymizationservice may be implemented within a trusted execution environment (TEE)of an organization's server, database, cloud platform, or the like.Furthermore, each instance of the anonymization service may have its ownidentity which can be proven through a digital certificate (e.g., X.509,or the like). For example, for each instance it can be proven that it isprotected with a trusted execution environment using remote attestation.An attestation together with the AS identity may be used to establishtrust in the correctness of the execution and the protection ofconfidentiality.

When an organization needs to anonymize a set of training data, theorganization transmits the training data to its respective anonymizationservice. In response, the anonymization service removes the PII from theraw training data to create anonymized data. In addition, theanonymization service also generates an authenticator object (alsoreferred to herein as simply an authenticator). The authenticator objectmay include a hash of the raw data, a hash of the anonymous data, and adigital signature over both hash values thereby binding the hash of theraw data and the hash of the anonymized data. In addition, theanonymization service may add its digital identity to the authenticatorobject and forward the anonymized data and the authenticator object tothe organizations computing node. In response, the computing node maystore the authenticator object on a blockchain and transmit theanonymized data to an aggregator node of a data processing pipeline(DPP).

The DPP may include one or more nodes (e.g., analytic nodes) fortraining a model. For example, an analytic node may include a singlemachine or a distributed processing cluster comprising simple computers(nodes) and/or specialized hardware. A software library or framework maybe responsible to schedule, execute, and aggregate processing jobs amongthe processing node(s) (in the cluster). Jobs may implement functions ofa (stateful) application, for example, training a machine learning modelor perform inference (e.g., text to speech/speech to text recognition,etc.) using a machine learning model. Additionally, the data processingpipeline may comprise local and distributed storage to support statefulapplications. The DPP also offers an interface to access and retrievethe result of processed jobs, e.g., retrieve the updated machinelearning model or retrieve the result of an inference. In someembodiments, the DPP may also include an aggregator node that aggregatestogether training data from multiple data owners.

In some embodiments, the anonymization service may validate the raw datausing various data properties including metadata and other data accessedfrom the organization's data stores. For example, the anonymizationservice may have access to the underlying database where the trainingdata is extracted from. In this case, the anonymization service mayverify that the correct data was used, and not fake data by comparingthe data to additional data pulled from the underlying database.

The aggregator node and the computing node of the organization may bothbe participants of the same blockchain network. Here, the anonymizationservice may be a smart contract or other software application that isinstalled and deployed on a blockchain peer within the blockchainnetwork (e.g., such as a peer of the organization). The aggregator nodemay receive the anonymized data from the computing node of theorganization (e.g., a blockchain peer) via a message or other request,and in response, query the blockchain for an authenticator object thatis associated with the anonymized data. For example, the hash of theanonymized data may be used as an identifier of the anonymized datawithin the query submitted by the aggregator node to the blockchain. Inresponse, the blockchain can provide the authenticator object to theaggregator node.

When the aggregator node has both the authenticator object from theblockchain and the anonymized data from the data owner/organization, theaggregator node verifies the signature of the anonymization service inthe aggregator object using the signer identity included in theaggregator object. For example, the aggregator node may check that thereceived anonymized data matches the data referenced in theauthenticator using hash comparison. Moreover, the aggregator checksthat the signer identity is also registered on the blockchain and thereexists a valid attestation, as described above. If these checks aresuccessful, the aggregator node may forward the validated anonymizeddata to the DPP. In the case that no authenticator is submitted for someanonymized data, the data will be dropped after some timeout. In somecases, the aggregator node is a first node within the DPP (which mayinclude one or more computing systems that train an analytic model).

Some of the benefits provided by the anonymization service describedherein include ensuring the correctness of anonymized training data,ensuring that the raw data does not leave the premises (e.g., when theanonymization service is implemented locally on a node of theorganization, etc.), validating that the anonymized data using theaggregator object, preventing fraud during a collaborative modeltraining process, ensuring that the correct anonymization mechanism isused via a trusted execution environment, and the like.

FIG. 1A illustrates a computing network 100 for anonymizing input datafor a data processing pipeline according to example embodiments.Referring to FIG. 1A, the computing network 100 may include a data owner110 (e.g., a computing node such as a server, database, cloud platform,etc.), a trusted execution environment (TEE) 120 that includes ananonymization service 122 according to various embodiments, a blockchain130, an aggregator node 140, and one or more analytic nodes 150. In someembodiments, the aggregator node 140 is the first node in the dataprocessing pipeline which includes the aggregator node 140 and one ormore analytic nodes 150. In this example, one data owner node 110 isshown. But it should be appreciated that the computing network 100 mayinclude a plurality of data owner nodes 110 (e.g., a consortium), whereeach data owner node 110 includes its own TEE 120 and instance of theanonymization service 122.

As described herein, the anonymization service 122 operating within theTEE 120 may anonymize data of the data owner node 110 that is to besubmitted for training an analytic model by the data processing pipelinesuch as a machine learning model, an artificial intelligence model, orthe like. Here, the anonymization service 122 may anonymize sensitivedata thereby preventing such data from being exposed to non-authorizedparties. For example, the anonymization service 122 may partially orcompletely remove personally identifiable information from the raw data.Also, data masking and obfuscation techniques could be used to anonymizethe data. For instance, a full customers address could be replaced withjust the country or postcode.

It should be appreciated that the example embodiments are not tied to aspecific use-case for data analytics. That is, the anonymized data canbe input for any data analytic pipeline that generates a machinelearning based application. For instance, the data may be used fortraining and re-training a machine learning model,federated/non-federated learning, and the like. Moreover, anonymizeddata can also be used as input for interference using machine learning.Examples of anonymized data include personal health information(personally identifiable information, sensitive personal data, e.g.,patients data), medical data, customers data (personal information),advertisement tracking information (commercially sensitive data, e.g.,locations, personal information), credit card information, and othertransaction data.

In an example embodiment, the anonymization service 122 is locatedwithin the security boundaries of the data owner node 110. For example,the anonymization service 122 can be deployed within a secure enclave ofa processor on the same node as the data owner node 110 or an on-premdata center node. Other setups are also possible, For example, theanonymization service may be deployed at a remote location from the dataowner node 110. In this example, the data owner node 110 may performremote attestation in order to verify that the anonymization service 122is indeed protected with TEE technology. Once verification succeeds, thedata owner node 110 and the anonymization service 122 may establish asecure communication channel to exchange the raw data to be anonymized.

In some embodiments, the anonymization service 122 may validate thetraining data (e.g., for correctness, etc.) prior to anonymizing thetraining data submitted by the data owner node 110. In this example, theanonymization service 122 can implement data validation in variousforms. The raw data can be checked for validity in the context of themachine learning application (e.g., a heart rate value is within acertain range, an address must have a valid postcode that matches thecity, etc.) In this case, if the data owner node 110 were to submit junkdata, the anonymization service 122 can validate the correctness of thedata (e.g., if the customer address is valid, etc.) and if validationfails, aborts the process. As another example, the anonymization service122 may leverage additional metadata to validate input (raw) data. Thismetadata can be either provided by the data owner node 110 with theinvocation of the anonymization service 122, or accessible by theanonymization service 122 during processing. For instance, when theanonymization service 122 needs to verify a bank account balance, it maycheck all existing transactions of the bank. Also, such metadata can beprovided as validation parameters during a bootstrapping process of theanonymization service 122 within the TEE 120.

In addition to anonymizing the raw data submitted by the data owner node110, the anonymization service 122 may generate an authenticator object(e.g., further described in the examples of FIGS. 4A and 4B) which canbe used to prove the anonymized data is valid data submitted by aregistered entity of the consortium/blockchain 130. For example, theauthenticator may be a structured message, data object, etc., such as anetwork message, an XML file, a CSV file, a data file, or the like. Theauthenticator may include i) a hash (h_(rd)) of the original data (i.e.,the raw data), ii) a hash (h_(ad)) of the anonymized data, iii) adigital signature over hash (h_(rd)∥h_(hd)), and iv) a signer identity.Note ∥ denotes the concatenation of the hash of the raw data and thehash of the anonymized data.

Both the anonymized data and the authenticator object may be returned tothe data owner node 110. In response, the data owner node 110 may storea blockchain transaction including the authenticator object to theblockchain 130 (e.g., a blockchain ledger that includes a hash-linkedchain of blocks and a state database, etc.) An auditor 160 (e.g., atrusted third-party, another data owner node, etc.) may retrieve theauthenticator object from the blockchain 130 should the need arise toauthenticate the anonymized data.

Furthermore, the data owner node 110 may provide the anonymized data tothe aggregator node 140. In addition, the aggregator node 140 maywait/listen for the authenticator object of the anonymized data to bestored as a transaction on the blockchain 130. For example, theaggregator node may query the blockchain 130 based on an identifier ofthe authenticator object that is extracted from anonymized data.

As an example, the identifier of the authenticator object may be a hashvalue of the anonymized data. Here, the aggregator node 140 may computethe hash of the received anonymized data and query the blockchain for anauthenticator object corresponding to the hash value of the anonymizeddata. Additionally, the aggregator can also subscribe at the blockchain130 to automatically receive a notification once a transaction has beencommitted comprising the authenticator object for the receivedanonymized data. A smart contract can implement this query functionalityand event notification.

Once the aggregator node 140 has obtained the anonymized data and theauthenticator object, the aggregator node 140 can verify/validate theanonymized data. If it is successfully validated, the aggregator node140 may forward the anonymized data to the data processing pipeline(e.g., analytic node 150). In some embodiments, the aggregator node 140is the first state of the data processing pipeline.

For example, the aggregator node 140 may verify the received anonymizeddata using the corresponding authenticator object. In some embodiments,the aggregator node 140 verifies the signature of the anonymizationservice 122 over the hash values using the signer identity. Inparticular, the aggregator node 140 may check that the receivedanonymized data matches the data referenced in the authenticator usinghash comparison. Moreover, the aggregator node 140 may check that thesigner identity is also registered on the blockchain and there exists avalid attestation. If these checks are successful, the aggregator node140 may forward the anonymized data to the data processing pipeline.Otherwise, the aggregator node 140 may terminate the process.

In some embodiments, the authenticator object may always remain on theblockchain. Optionally, the authenticator object could be extended withthe data owner to allow the aggregator node 140 to reach out to the dataowner in case an authenticator object has been committed and theanonymized data got lost during transmission. The owner's identity canalso be implemented with the transaction author identity.

Authenticator objects may always remain on the blockchain 130. Asanother example, the authenticator could be extended by the data ownernode 110 to allow the aggregator node 140 to reach out to the data ownernode 110 for the authenticator object. The owner's identity can also beimplemented with the transaction author identity. The aggregator node140 may also have limited buffering capacity (even though storage ofseveral hundreds of terabytes and more is feasible today) therefore,anonymized data is dropped after some timeout. Another strategy may bethat the aggregator blocks accepting new anonymized data until data isforwarded to the DPP. Horizontal scaling of the aggregator node 140 isanother approach to master huge volumes of anonymized data.

FIG. 1B illustrates a network 170 of data owner nodes that participatein training a model according to example embodiments. Here, the network170 includes a consortium of data owner nodes that are collaborating ontraining a model. Referring to FIG. 1B, four data owner nodes 110A,110B, 110C, and 110D provide respective data for training a machinelearning model via the data analytic node 150. In this example, each ofthe four data owner nodes 110A, 110B, 110C, and 110D includes its ownanonymization service instance 122A, 122B, 122C, and 122D, respectively.Here, each of the data owner nodes 110A, 110B, 110C, and 110D, mayinclude a TEE (e.g., a secure enclave, etc.) where the anonymizationservice is installed and running. In this example, the aggregator node140 may be included within a blockchain network with the data ownernodes 110A-110D. Furthermore, the aggregator node 140 may aggregateanonymized training data that is received directly from the data ownernodes 110A-110D and forward it to the analytic node, after successfulverification.

FIG. 2A illustrates a blockchain architecture configuration 200,according to example embodiments. Referring to FIG. 2A, the blockchainarchitecture 200 may include certain blockchain elements, for example, agroup of blockchain nodes 202. The blockchain nodes 202 may include oneor more nodes 204-210 (these four nodes are depicted by example only).These nodes participate in a number of activities, such as blockchaintransaction addition and validation process (consensus). One or more ofthe blockchain nodes 204-210 may endorse transactions based onendorsement policy and may provide an ordering service for allblockchain nodes in the architecture 200. A blockchain node may initiatea blockchain authentication and seek to write to a blockchain immutableledger stored in blockchain layer 216, a copy of which may also bestored on the underpinning physical infrastructure 214. The blockchainconfiguration may include one or more applications 224 which are linkedto application programming interfaces (APIs) 222 to access and executestored program/application code 220 (e.g., chaincode, smart contracts,etc.) which can be created according to a customized configurationsought by participants and can maintain their own state, control theirown assets, and receive external information. This can be deployed as atransaction and installed, via appending to the distributed ledger, onall blockchain nodes 204-210.

The blockchain base or platform 212 may include various layers ofblockchain data, services (e.g., cryptographic trust services, virtualexecution environment, etc.), and underpinning physical computerinfrastructure that may be used to receive and store new transactionsand provide access to auditors which are seeking to access data entries.The blockchain layer 216 may expose an interface that provides access tothe virtual execution environment necessary to process the program codeand engage the physical infrastructure 214. Cryptographic trust services218 may be used to verify transactions such as asset exchangetransactions and keep information private.

The blockchain architecture configuration of FIG. 2A may process andexecute program/application code 220 via one or more interfaces exposed,and services provided, by blockchain platform 212. The code 220 maycontrol blockchain assets. For example, the code 220 can store andtransfer data, and may be executed by nodes 204-210 in the form of asmart contract and associated chaincode with conditions or other codeelements subject to its execution. As a non-limiting example, smartcontracts may be created to execute reminders, updates, and/or othernotifications subject to the changes, updates, etc. The smart contractscan themselves be used to identify rules associated with authorizationand access requirements and usage of the ledger. For example, the smartcontract (or chaincode executing the logic of the smart contract) mayread blockchain data 226 which may be processed by one or moreprocessing entities (e.g., virtual machines) included in the blockchainlayer 216 to generate results 228 including alerts, determiningliability, and the like, within a complex service scenario. The physicalinfrastructure 214 may be utilized to retrieve any of the data orinformation described herein.

A smart contract may be created via a high-level application andprogramming language, and then written to a block in the blockchain. Thesmart contract may include executable code which is registered, stored,and/or replicated with a blockchain (e.g., distributed network ofblockchain peers). A transaction is an execution of the smart contractlogic which can be performed in response to conditions associated withthe smart contract being satisfied. The executing of the smart contractmay trigger a trusted modification(s) to a state of a digital blockchainledger. The modification(s) to the blockchain ledger caused by the smartcontract execution may be automatically replicated throughout thedistributed network of blockchain peers through one or more consensusprotocols.

The smart contract may write data to the blockchain in the format ofkey-value pairs. Furthermore, the smart contract code can read thevalues stored in a blockchain and use them in application operations.The smart contract code can write the output of various logic operationsinto one or more blocks within the blockchain. The code may be used tocreate a temporary data structure in a virtual machine or othercomputing platform. Data written to the blockchain can be public and/orcan be encrypted and maintained as private. The temporary data that isused/generated by the smart contract is held in memory by the suppliedexecution environment, then deleted once the data needed for theblockchain is identified.

A chaincode may include the code interpretation (e.g., the logic) of asmart contract. For example, the chaincode may include a packaged anddeployable version of the logic within the smart contract. As describedherein, the chaincode may be program code deployed on a computingnetwork, where it is executed and validated by chain validators togetherduring a consensus process. The chaincode may receive a hash andretrieve from the blockchain a hash associated with the data templatecreated by use of a previously stored feature extractor. If the hashesof the hash identifier and the hash created from the stored identifiertemplate data match, then the chaincode sends an authorization key tothe requested service. The chaincode may write to the blockchain dataassociated with the cryptographic details.

FIG. 2B illustrates an example of a blockchain transactional flow 250between nodes of the blockchain in accordance with an exampleembodiment. Referring to FIG. 2B, the transaction flow may include aclient node 260 transmitting a transaction proposal 291 to an endorsingpeer node 281. The endorsing peer 281 may verify the client signatureand execute a chaincode function to initiate the transaction. The outputmay include the chaincode results, a set of key/value versions that wereread in the chaincode (read set), and the set of keys/values that werewritten in chaincode (write set). Here, the endorsing peer 281 maydetermine whether or not to endorse the transaction proposal. Theproposal response 292 is sent back to the client 260 along with anendorsement signature, if approved. The client 260 assembles theendorsements into a transaction payload 293 and broadcasts it to anordering service node 284. The ordering service node 284 then deliversordered transactions as blocks to all peers 281-283 on a channel. Beforecommittal to the blockchain, each peer 281-283 may validate thetransaction. For example, the peers may check the endorsement policy toensure that the correct allotment of the specified peers have signed theresults and authenticated the signatures against the transaction payload293.

Referring again to FIG. 2B, the client node initiates the transaction291 by constructing and sending a request to the peer node 281, which isan endorser. The client 260 may include an application leveraging asupported software development kit (SDK), which utilizes an availableAPI to generate a transaction proposal. The proposal is a request toinvoke a chaincode function so that data can be read and/or written tothe ledger (i.e., write new key value pairs for the assets). The SDK mayserve as a shim to package the transaction proposal into a properlyarchitected format (e.g., protocol buffer over a remote procedure call(RPC)) and take the client's cryptographic credentials to produce aunique signature for the transaction proposal.

In response, the endorsing peer node 281 may verify (a) that thetransaction proposal is well formed, (b) the transaction has not beensubmitted already in the past (replay-attack protection), (c) thesignature is valid, and (d) that the submitter (client 260, in theexample) is properly authorized to perform the proposed operation onthat channel. The endorsing peer node 281 may take the transactionproposal inputs as arguments to the invoked chaincode function. Thechaincode is then executed against a current state database to producetransaction results including a response value, read set, and write set.However, no updates are made to the ledger at this point. In 292, theset of values, along with the endorsing peer node's 281 signature ispassed back as a proposal response 292 to the SDK of the client 260which parses the payload for the application to consume.

In response, the application of the client 260 inspects/verifies thesignatures of the endorsing peers and compares the proposal responses todetermine if the proposal response is the same. If the chaincode onlyqueried the ledger, the application would inspect the query response andwould typically not submit the transaction to the ordering node service284. If the client application intends to submit the transaction to theordering node service 284 to update the ledger, the applicationdetermines if the specified endorsement policy has been fulfilled beforesubmitting (i.e., did all peer nodes necessary for the transactionendorse the transaction). Here, the client may include only one ofmultiple parties to the transaction. In this case, each client may havetheir own endorsing node, and each endorsing node will need to endorsethe transaction. The architecture is such that even if an applicationselects not to inspect responses or otherwise forwards an unendorsedtransaction, the endorsement policy will still be enforced by peers andupheld at the commit validation phase.

After successful inspection, in step 293 the client 260 assemblesendorsements into a transaction proposal and broadcasts the transactionproposal and response within a transaction message to the ordering node284. The transaction may contain the read/write sets, the endorsing peersignatures and a channel ID. The ordering node 284 does not need toinspect the entire content of a transaction in order to perform itsoperation, instead the ordering node 284 may simply receive transactionsfrom all channels in the network, order them chronologically by channel,and create blocks of transactions per channel.

The blocks are delivered from the ordering node 284 to all peer nodes281-283 on the channel. The data section within the block may bevalidated to ensure an endorsement policy is fulfilled and to ensurethat there have been no changes to ledger state for read set variablessince the read set was generated by the transaction execution.Furthermore, in step 295 each peer node 281-283 appends the block to thechannel's chain, and for each valid transaction the write sets arecommitted to current state database. An event may be emitted, to notifythe client application that the transaction (invocation) has beenimmutably appended to the chain, as well as to notify whether thetransaction was validated or invalidated.

In the example of FIG. 2B, the client node 260 and each of theblockchain peers 281-284 may use a verifiable credential as a signature.As the transaction moves through the different steps of FIG. 2B, each ofthe client node 260 and the blockchain peers 281-284 may attach theirrespective VC to a step that they have performed. In this example, eachof the blockchain peers 281-284 may include a set of VCs (e.g., one ormore VCs) that provide identity and membership information associatedwith the blockchain peers 281-284. For example, the client node 260 mayinclude a verifiable certificate with a claim issued by a MSP of theblockchain network that identifies the client as a member fortransacting on the blockchain. As another example, the blockchain peers281-283 may include VCs that identify the blockchain peers 281-283 asendorsing peers of the blockchain. Meanwhile, the blockchain peer 284may include a VC that identifies the blockchain peer 284 as an orderingnode of the blockchain. Many other VCs are possible. For example,particular channels on the blockchain (e.g., different blockchains onthe same ledger) may require different VCs in order to serve as aclient, a peer, an endorser, and orderer, and the like. As anotherexample, different types of transactions and/or chaincodes may require aseparate VC by the clients, the peers, etc. For example, a client mayonly submit a transaction to invoke a particular chaincode if the clienthas a VC identifying the client has authority to use such chaincode.

FIG. 3A illustrates an example of a permissioned blockchain network 300,which features a distributed, decentralized peer-to-peer architecture.In this example, a blockchain user 302 may initiate a transaction to thepermissioned blockchain 304. In this example, the transaction can be adeploy, invoke, or query, and may be issued through a client-sideapplication leveraging an SDK, directly through an API, etc. Networksmay provide access to a regulator 306, such as an auditor. A blockchainnetwork operator 308 manages member permissions, such as enrolling theregulator 306 as an “auditor” and the blockchain user 302 as a “client”.An auditor could be restricted only to querying the ledger whereas aclient could be authorized to deploy, invoke, and query certain types ofchaincode.

A blockchain developer 310 can write chaincode and client-sideapplications. The blockchain developer 310 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 312 in chaincode, the developer 310 could use anout-of-band connection to access the data. In this example, theblockchain user 302 connects to the permissioned blockchain 304 througha peer node 314. Before proceeding with any transactions, the peer node314 retrieves the user's enrollment and transaction certificates from acertificate authority 316, which manages user roles and permissions. Insome cases, blockchain users must possess these digital certificates inorder to transact on the permissioned blockchain 304. Meanwhile, a userattempting to utilize chaincode may be required to verify theircredentials on the traditional data source 312. To confirm the user'sauthorization, chaincode can use an out-of-band connection to this datathrough a traditional processing platform 318.

FIG. 3B illustrates another example of a permissioned blockchain network320, which features a distributed, decentralized peer-to-peerarchitecture. In this example, a blockchain user 322 may submit atransaction to the permissioned blockchain 324. In this example, thetransaction can be a deploy, invoke, or query, and may be issued througha client-side application leveraging an SDK, directly through an API,etc. Networks may provide access to a regulator 326, such as an auditor.A blockchain network operator 328 manages member permissions, such asenrolling the regulator 326 as an “auditor” and the blockchain user 322as a “client”. An auditor could be restricted only to querying theledger whereas a client could be authorized to deploy, invoke, and querycertain types of chaincode.

A blockchain developer 330 writes chaincode and client-sideapplications. The blockchain developer 330 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 332 in chaincode, the developer 330 could use anout-of-band connection to access the data. In this example, theblockchain user 322 connects to the network through a peer node 334.Before proceeding with any transactions, the peer node 334 retrieves theuser's enrollment and transaction certificates from the certificateauthority 336. In some cases, blockchain users must possess thesedigital certificates in order to transact on the permissioned blockchain324. Meanwhile, a user attempting to utilize chaincode may be requiredto verify their credentials on the traditional data source 332. Toconfirm the user's authorization, chaincode can use an out-of-bandconnection to this data through a traditional processing platform 338.

In some embodiments, the blockchain herein may be a permissionlessblockchain. In contrast with permissioned blockchains which requirepermission to join, anyone can join a permissionless blockchain. Forexample, to join a permissionless blockchain a user may create apersonal address and begin interacting with the network, by submittingtransactions, and hence adding entries to the ledger. Additionally, allparties have the choice of running a node on the system and employingthe mining protocols to help verify transactions.

FIG. 3C illustrates a process 350 of a transaction being processed by apermissionless blockchain 352 including a plurality of nodes 354. Asender 356 desires to send payment or some other form of value (e.g., adeed, medical records, a contract, a good, a service, or any other assetthat can be encapsulated in a digital record) to a recipient 358 via thepermissionless blockchain 352. In one embodiment, each of the senderdevice 356 and the recipient device 358 may have digital wallets(associated with the blockchain 352) that provide user interfacecontrols and a display of transaction parameters. In response, thetransaction is broadcast throughout the blockchain 352 to the nodes 354.Depending on the blockchain's 352 network parameters the nodes verify360 the transaction based on rules (which may be pre-defined ordynamically allocated) established by the permissionless blockchain 352creators. For example, this may include verifying identities of theparties involved, etc. The transaction may be verified immediately or itmay be placed in a queue with other transactions and the nodes 354determine if the transactions are valid based on a set of network rules.

In structure 362, valid transactions are formed into a block and sealedwith a lock (hash). This process may be performed by mining nodes amongthe nodes 354. Mining nodes may utilize additional software specificallyfor mining and creating blocks for the permissionless blockchain 352.Each block may be identified by a hash (e.g., 256 bit number, etc.)created using an algorithm agreed upon by the network. Each block mayinclude a header, a pointer or reference to a hash of a previous block'sheader in the chain, and a group of valid transactions. The reference tothe previous block's hash is associated with the creation of the secureindependent chain of blocks.

Before blocks can be added to the blockchain, the blocks must bevalidated. Validation for the permissionless blockchain 352 may includea proof-of-work (PoW) which is a solution to a puzzle derived from theblock's header. Although not shown in the example of FIG. 3C, anotherprocess for validating a block is proof-of-stake. Unlike theproof-of-work, where the algorithm rewards miners who solve mathematicalproblems, with the proof of stake, a creator of a new block is chosen ina deterministic way, depending on its wealth, also defined as “stake.”Then, a similar proof is performed by the selected/chosen node.

With mining 364, nodes try to solve the block by making incrementalchanges to one variable until the solution satisfies a network-widetarget. This creates the PoW thereby ensuring correct answers. In otherwords, a potential solution must prove that computing resources weredrained in solving the problem. In some types of permissionlessblockchains, miners may be rewarded with value (e.g., coins, etc.) forcorrectly mining a block.

Here, the PoW process, alongside the chaining of blocks, makesmodifications of the blockchain extremely difficult, as an attacker mustmodify all subsequent blocks in order for the modifications of one blockto be accepted. Furthermore, as new blocks are mined, the difficulty ofmodifying a block increases, and the number of subsequent blocksincreases. With distribution 366, the successfully validated block isdistributed through the permissionless blockchain 352 and all nodes 354add the block to a majority chain which is the permissionlessblockchain's 352 auditable ledger. Furthermore, the value in thetransaction submitted by the sender 356 is deposited or otherwisetransferred to the digital wallet of the recipient device 358.

FIG. 4A illustrates a process 400A of generating an authenticator 430for authenticating anonymized data of a data owner 410 according toexample embodiments, and FIG. 4B illustrates a process 400B ofvalidating anonymized data based on the authenticator 430 according toexample embodiments. Referring to FIG. 4A, the data owner node 410 maybe coupled to an anonymization service 422 installed and executinginside of a trusted execution environment (TEE) 420 of the data ownernode 410 or another node on premises. As another example, theanonymization service 422 may be on a remote system. Here, the dataowner node 410 and the anonymization service 422 may establish a securechannel between each other using TLS, or the like. The anonymizationservice 422 may receive a data set for anonymization. The data set mayinclude a document, a message, a spreadsheet, a table, or the like. Thedata set may include personally-identifiable information. In response,the anonymization service 422 may generate an authenticator 430. Theauthenticator 430 may include a message, a file, a document, a blob, orsome other data object, which can be used to authenticate the data setafter it has been anonymized by the anonymization service.

The authenticator 430 may include multiple fields with different valuesstored therein by the anonymization service 422. For example, theanonymization service 422 may generate and store a hash value (e.g., 256bits, 128 bits, etc.) in a field 431 that is created by hashing the datareceived from the data owner node. As another example, the anonymizationservice 422 may anonymize the data and create a hash value of theanonymized data. In this case, the hash value of the anonymized data maybe stored in a field 432. The anonymization service 422 may generate asignature over the hash value of the data stored in field 431 and thehash value of the anonymized data stored in field 432, and store thesignature in a field 433. In addition, the anonymization service 422 mayadd a signer identity of the anonymization service 422 to a field 434 ofthe authenticator. The anonymization service 422 may provide theauthenticator 430 along with anonymized data to the data owner node 410.

For example, the signer identity stored in field 434 may denote aninstance of the anonymization service and may include a publickey/certificate such as an X.509 certificate or the like issued by anauthority. When a new anonymization service instance is started(bootstrapping), the anonymization service may generate the public key.Here, the data owner or a service provider may initiate the remoteattestation protocol with the anonymization service instance. That is, achallenger may send an attestation request (containing a nonce to ensurefreshness) to the anonymization service instance. Once the anonymizationservice receives such a request, it produces a cryptographic proof thatshows that the anonymization service is hosted in a Trusted ExecutionEnvironment and provisioned with a specific software (e.g., ananonymization algorithm, etc.) and data (e.g., validation parameters,etc.).

In this example, the proof may include a hash of the application code,also referred to as code identity, that is running inside the TEE. Inaddition, the proof may contain a hash of the anonymization servicepublic key, a hash of the validation parameters, and the request nonce.The proof and the public key of the anonymization service are returnedto the challenger, which then verifies the proof. That is, thechallenger first verifies that the proof was generated by a TEE. Next,the challenger checks that the proof corresponds to expected codeidentity, expected validation parameters, nonce, and the public keyreturned by the anonymization service.

In this example, the code identity and the validation paraments may beavailable to the challenger, for instance, via the blockchain where allparticipants (consortium) have agreed on the parameters upfront. Onceremote attestation protocol succeeds, the public key (identity) and thecorresponding proof are also stored on the blockchain to make itaccessible to other participants. There may exist a smart contract thatperforms the validation of the proof before storing it on theblockchain. This ensures that only valid proofs are registered. Theaggregator node can also query a smart contract to check if a signeridentity is a valid anonymization service, that is, an anonymizationservice instance with a valid public key and a valid proof that runs theexpected anonymization service software, with the expected validationparameters, within a proper trusted execution environment.

Referring again to FIG. 4A, the data owner node 410 may run a softwareor software package which contains a plurality of modules. For example,a first module may be used to communicate with the anonymization service422. This communication can be realized as socket communication, processcommunication, or via any form of Web application programming interface(API). This communication may be protected via a secure communicationchannel (e.g., TLS) that protects the confidentiality and integrity ofthe data in transient. A second module may be a blockchain client tosubmit the authenticator 430 to the blockchain as a transaction. In someembodiments, if the anonymization service is implemented using a smartcontract, the first module and the second module can be merged into asingle module. Nevertheless, communication with the blockchain (peer)may be protected via secure communication. As another example, a thirdmodule may be responsible to transmit the anonymized data to theaggregator. This can be realized as storage client, message queueclient, web API, etc.

Referring to FIG. 4B, an aggregator node 440 may receive anonymized data436 from the data owner node 410 in FIG. 4A. Furthermore, the aggregatornode 440 may detect when the corresponding authenticator 430 of theanonymized data 436 has been stored to the blockchain (not shown). Here,the aggregator node 440 may use an identifier from the anonymized data,such as a hash of the anonymized data 436, and query the blockchain forthe authenticator 430 that also includes the hash of the anonymized data436. In response, the blockchain may return the authenticator 430.

Once the aggregator node 440 has obtained the anonymized data 436 andthe authenticator 430, the aggregator node 440 can verify/validate theanonymized data 436. If it is successfully validated, the aggregatornode 440 may forward the anonymized data 436 to the data processingpipeline. In some embodiments, the aggregator node 440 is the firststate of the data processing pipeline.

For example, the aggregator node 440 may perform a verification process460. For example, in 461, the aggregator node 440 may recompute the hashof the anonymized data and compare the recomputed hash to the hash ofthe anonymized data stored in the filed 432 of the authenticator 430, in462. In some embodiments, the aggregator node 440 verifies the signatureof the anonymization service 422 stored in the field 433 over the hashvalues using the signer identity stored in the field 434. In particular,the aggregator node 440 may check that the signer identity is alsoregistered on the blockchain and there exists a valid attestation. Ifthese checks are successful, the aggregator node 440 may forward theanonymized data 436 to the data processing pipeline. Otherwise, theaggregator node 440 may terminate the process.

FIG. 5 illustrates a method 500 for authenticating anonymized dataaccording to example embodiments. For example, the method 500 may beperformed by a blockchain network that includes a data owner node and atrusted execution environment such as a secure enclave. Referring toFIG. 5, in 510, the method may include anonymizing, via an anonymizationservice hosted within a trusted execution environment (TEE), raw dataprovided by a computing node to generate anonymized data. For example,the anonymization service may be hosted within a secure enclave of ahardware processor of at least one of the computing nodes and a remotenode with respect to the computing node.

In 520, the method may include generating, via the anonymizationservice, an authenticator object that binds together a hash of the rawdata and a hash of the anonymized data. In 530, the method may includetransmitting the generated anonymized data to the computing node, and in540, the method may include submitting the authenticator object to ablockchain ledger via a blockchain transaction. For example, theauthenticator object may be stored within a blockchain transaction thatis submitted to a permissioned blockchain network for storage on ablockchain managed therein.

In some embodiments, the generating may also include a process of addinga hash of the raw data to a first field of the authenticator object,adding a hash of the anonymized data to a second field of theauthenticator object, and adding a cryptographic signature over the hashof the raw data and the hash of the anonymized data to a third field ofthe authenticator object. In some embodiments, the method may furtherinclude adding a digital certificate of the anonymization service to afourth field of the authenticator object prior to submitting theauthenticator object to the blockchain ledger.

In some embodiments, the method may further include receiving, via anaggregator node, the anonymized data from the computing node, andquerying, via the aggregator node, the blockchain ledger for theauthenticator object that has been stored to the blockchain ledger. Insome embodiments, the method may further include validating, via theaggregator node, the anonymized data from the computing node based onthe authenticator object stored on the blockchain ledger, andtransmitting the validated anonymized data to a data processingpipeline.

In some embodiments, the generating may also include a process ofconcatenating hash inputs used to create the hash of the raw data andthe hash of the anonymized data, and signing the concatenated hashinputs with a digital signature of the authenticator service to createthe cryptographic signature. In some embodiments, the method may furtherinclude receiving, via the anonymization service, a challenge requestfrom the computing node, and in response, transmitting, via theanonymization service, cryptographic proof that the anonymizationservice is hosted in the TEE.

FIG. 6A illustrates an example system 600 that includes a physicalinfrastructure 610 configured to perform various operations according toexample embodiments. Referring to FIG. 6A, the physical infrastructure610 includes a module 612 and a module 614. The module 614 includes ablockchain 620 and a smart contract 630 (which may reside on theblockchain 620), that may execute any of the operational steps 608 (inmodule 612) included in any of the example embodiments. Thesteps/operations 608 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 630 and/orblockchains 620. The physical infrastructure 610, the module 612, andthe module 614 may include one or more computers, servers, processors,memories, and/or wireless communication devices. Further, the module 612and the module 614 may be a same module.

FIG. 6B illustrates another example system 640 configured to performvarious operations according to example embodiments. Referring to FIG.6B, the system 640 includes a module 612 and a module 614. The module614 includes a blockchain 620 and a smart contract 630 (which may resideon the blockchain 620), that may execute any of the operational steps608 (in module 612) included in any of the example embodiments. Thesteps/operations 608 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 630 and/orblockchains 620. The physical infrastructure 610, the module 612, andthe module 614 may include one or more computers, servers, processors,memories, and/or wireless communication devices. Further, the module 612and the module 614 may be a same module.

FIG. 6C illustrates an example system configured to utilize a smartcontract configuration among contracting parties and a mediating serverconfigured to enforce the smart contract terms on the blockchainaccording to example embodiments. Referring to FIG. 6C, theconfiguration 650 may represent a communication session, an assettransfer session or a process or procedure that is driven by a smartcontract 630 which explicitly identifies one or more user devices 652and/or 656. The execution, operations and results of the smart contractexecution may be managed by a server 654. Content of the smart contract630 may require digital signatures by one or more of the entities 652and 656 which are parties to the smart contract transaction. The resultsof the smart contract execution may be written to a blockchain 620 as ablockchain transaction. The smart contract 630 resides on the blockchain620 which may reside on one or more computers, servers, processors,memories, and/or wireless communication devices.

FIG. 6D illustrates a system 660 including a blockchain, according toexample embodiments. Referring to the example of FIG. 6D, an applicationprogramming interface (API) gateway 662 provides a common interface foraccessing blockchain logic (e.g., smart contract 630 or other chaincode)and data (e.g., distributed ledger, etc.). In this example, the APIgateway 662 is a common interface for performing transactions (invoke,queries, etc.) on the blockchain by connecting one or more entities 652and 656 to a blockchain peer (i.e., server 654). Here, the server 654 isa blockchain network peer component that holds a copy of the world stateand a distributed ledger allowing clients 652 and 656 to query data onthe world state as well as submit transactions into the blockchainnetwork where, depending on the smart contract 630 and endorsementpolicy, endorsing peers will run the smart contracts 630.

The above embodiments may be implemented in hardware, in a computerprogram executed by a processor, in firmware, or in a combination of theabove. A computer program may be embodied on a computer readable medium,such as a storage medium. For example, a computer program may reside inrandom access memory (“RAM”), flash memory, read-only memory (“ROM”),erasable programmable read-only memory (“EPROM”), electrically erasableprogrammable read-only memory (“EEPROM”), registers, hard disk, aremovable disk, a compact disk read-only memory (“CD-ROM”), or any otherform of storage medium known in the art.

An exemplary storage medium may be coupled to the processor such thatthe processor may read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anapplication specific integrated circuit (“ASIC”). In the alternative,the processor and the storage medium may reside as discrete components.

FIG. 7A illustrates a process 700 of a new block being added to adistributed ledger 720, according to example embodiments, and FIG. 7Billustrates contents of a new data block structure 730 for blockchain,according to example embodiments. Referring to FIG. 7A, clients (notshown) may submit transactions to blockchain nodes 711, 712, and/or 713.Clients may be instructions received from any source to enact activityon the blockchain 720. As an example, clients may be applications thatact on behalf of a requester, such as a device, person or entity topropose transactions for the blockchain. The plurality of blockchainpeers (e.g., blockchain nodes 711, 712, and 713) may maintain a state ofthe blockchain network and a copy of the distributed ledger 720.Different types of blockchain nodes/peers may be present in theblockchain network including endorsing peers which simulate and endorsetransactions proposed by clients and committing peers which verifyendorsements, validate transactions, and commit transactions to thedistributed ledger 720. In this example, the blockchain nodes 711, 712,and 713 may perform the role of endorser node, committer node, or both.

The distributed ledger 720 includes a blockchain which stores immutable,sequenced records in blocks, and a state database 724 (current worldstate) maintaining a current state of the blockchain 722. Onedistributed ledger 720 may exist per channel and each peer maintains itsown copy of the distributed ledger 720 for each channel of which theyare a member. The blockchain 722 is a transaction log, structured ashash-linked blocks where each block contains a sequence of Ntransactions. Blocks may include various components such as shown inFIG. 7B. The linking of the blocks (shown by arrows in FIG. 7A) may begenerated by adding a hash of a prior block's header within a blockheader of a current block. In this way, all transactions on theblockchain 722 are sequenced and cryptographically linked togetherpreventing tampering with blockchain data without breaking the hashlinks. Furthermore, because of the links, the latest block in theblockchain 722 represents every transaction that has come before it. Theblockchain 722 may be stored on a peer file system (local or attachedstorage), which supports an append-only blockchain workload.

The current state of the blockchain 722 and the distributed ledger 722may be stored in the state database 724. Here, the current state datarepresents the latest values for all keys ever included in the chaintransaction log of the blockchain 722. Chaincode invocations executetransactions against the current state in the state database 724. Tomake these chaincode interactions extremely efficient, the latest valuesof all keys are stored in the state database 724. The state database 724may include an indexed view into the transaction log of the blockchain722, it can therefore be regenerated from the chain at any time. Thestate database 724 may automatically get recovered (or generated ifneeded) upon peer startup, before transactions are accepted.

Endorsing nodes receive transactions from clients and endorse thetransaction based on simulated results. Endorsing nodes hold smartcontracts which simulate the transaction proposals. When an endorsingnode endorses a transaction, the endorsing nodes creates a transactionendorsement which is a signed response from the endorsing node to theclient application indicating the endorsement of the simulatedtransaction. The method of endorsing a transaction depends on anendorsement policy which may be specified within chaincode. An exampleof an endorsement policy is “the majority of endorsing peers mustendorse the transaction”. Different channels may have differentendorsement policies. Endorsed transactions are forward by the clientapplication to ordering service 710.

The ordering service 710 accepts endorsed transactions, orders them intoa block, and delivers the blocks to the committing peers. For example,the ordering service 710 may initiate a new block when a threshold oftransactions has been reached, a timer times out, or another condition.In the example of FIG. 7A, blockchain node 712 is a committing peer thathas received a new data new data block 730 for storage on blockchain720. The first block in the blockchain may be referred to as a genesisblock which includes information about the blockchain, its members, thedata stored therein, etc.

The ordering service 710 may be made up of a cluster of orderers. Theordering service 710 does not process transactions, smart contracts, ormaintain the shared ledger. Rather, the ordering service 710 may acceptthe endorsed transactions and specifies the order in which thosetransactions are committed to the distributed ledger 720. Thearchitecture of the blockchain network may be designed such that thespecific implementation of ‘ordering’ (e.g., Solo, Kafka, BFT, etc.)becomes a pluggable component.

Transactions are written to the distributed ledger 720 in a consistentorder. The order of transactions is established to ensure that theupdates to the state database 724 are valid when they are committed tothe network. Unlike a cryptocurrency blockchain system (e.g., Bitcoin,etc.) where ordering occurs through the solving of a cryptographicpuzzle, or mining, in this example the parties of the distributed ledger720 may choose the ordering mechanism that best suits that network.

When the ordering service 710 initializes a new data block 730, the newdata block 730 may be broadcast to committing peers (e.g., blockchainnodes 711, 712, and 713). In response, each committing peer validatesthe transaction within the new data block 730 by checking to make surethat the read set and the write set still match the current world statein the state database 724. Specifically, the committing peer candetermine whether the read data that existed when the endorserssimulated the transaction is identical to the current world state in thestate database 724. When the committing peer validates the transaction,the transaction is written to the blockchain 722 on the distributedledger 720, and the state database 724 is updated with the write datafrom the read-write set. If a transaction fails, that is, if thecommitting peer finds that the read-write set does not match the currentworld state in the state database 724, the transaction ordered into ablock will still be included in that block, but it will be marked asinvalid, and the state database 724 will not be updated.

Referring to FIG. 7B, a new data block 730 (also referred to as a datablock) that is stored on the blockchain 722 of the distributed ledger720 may include multiple data segments such as a block header 740, blockdata 750 (block data section), and block metadata 760. It should beappreciated that the various depicted blocks and their contents, such asnew data block 730 and its contents, shown in FIG. 7B are merelyexamples and are not meant to limit the scope of the exampleembodiments. In a conventional block, the data section may storetransactional information of N transaction(s) (e.g., 1, 10, 100, 500,1000, 2000, 3000, etc.) within the block data 750.

The new data block 730 may include a link to a previous block (e.g., onthe blockchain 722 in FIG. 7A) within the block header 740. Inparticular, the block header 740 may include a hash of a previousblock's header. The block header 740 may also include a unique blocknumber, a hash of the block data 750 of the new data block 730, and thelike. The block number of the new data block 730 may be unique andassigned in various orders, such as an incremental/sequential orderstarting from zero.

According to various embodiments, the block data 750 may store anauthenticator object 752 such as that generated by the anonymizationservice described herein. For example, the authenticator object 752 maybe stored within a write set of the block data 750, however, embodimentsare not limited thereto. Thus, the authenticator object 752 can bestored in an immutable log of blocks on the distributed ledger 720. Someof the benefits of the authenticator object 752 on the blockchain arereflected in the various embodiments disclosed and depicted herein.Although in FIG. 7B, the authenticator object 752 is depicted in thewrite set of the block data 750, in other embodiments, the authenticatorobject 752 may be located in the block header 740 or the block metadata760.

The block metadata 760 may store multiple fields of metadata (e.g., as abyte array, etc.). Metadata fields may include signature on blockcreation, a reference to a last configuration block, a transactionfilter identifying valid and invalid transactions within the block, lastoffset persisted of an ordering service that ordered the block, and thelike. The signature, the last configuration block, and the orderermetadata may be added by the ordering service 710. Meanwhile, acommitter of the block (such as blockchain node 712) may addvalidity/invalidity information based on an endorsement policy,verification of read/write sets, and the like. The transaction filtermay include a byte array of a size equal to the number of transactionsthat are included in the block data 750 and a validation codeidentifying whether a transaction was valid/invalid.

FIG. 7C illustrates an embodiment of a blockchain 770 for digitalcontent in accordance with the embodiments described herein. The digitalcontent may include one or more files and associated information. Thefiles may include media, images, video, audio, text, links, graphics,animations, web pages, documents, or other forms of digital content. Theimmutable, append-only aspects of the blockchain serve as a safeguard toprotect the integrity, validity, and authenticity of the digitalcontent, making it suitable use in legal proceedings where admissibilityrules apply or other settings where evidence is taken into considerationor where the presentation and use of digital information is otherwise ofinterest. In this case, the digital content may be referred to asdigital evidence.

The blockchain may be formed in various ways. In one embodiment, thedigital content may be included in and accessed from the blockchainitself. For example, each block of the blockchain may store a hash valueof reference information (e.g., header, value, etc.) along theassociated digital content. The hash value and associated digitalcontent may then be encrypted together. Thus, the digital content ofeach block may be accessed by decrypting each block in the blockchain,and the hash value of each block may be used as a basis to reference aprevious block. This may be illustrated as follows:

Block 1 Block 2 . . . Block N Hash Value 1 Hash Value 2 Hash Value NDigital Content 1 Digital Content 2 Digital Content N

In one embodiment, the digital content may be not included in theblockchain. For example, the blockchain may store the encrypted hashesof the content of each block without any of the digital content. Thedigital content may be stored in another storage area or memory addressin association with the hash value of the original file. The otherstorage area may be the same storage device used to store the blockchainor may be a different storage area or even a separate relationaldatabase. The digital content of each block may be referenced oraccessed by obtaining or querying the hash value of a block of interestand then looking up that has value in the storage area, which is storedin correspondence with the actual digital content. This operation may beperformed, for example, a database gatekeeper. This may be illustratedas follows:

Blockchain Storage Area Block 1 Hash Value Block 1 Hash Value . . .Content . . . . . . Block N Hash Value Block N Hash Value . . . Content

In the example embodiment of FIG. 7C, the blockchain 770 includes anumber of blocks 778 ₁, 778 ₂, . . . 778 _(N) cryptographically linkedin an ordered sequence, where N≥1. The encryption used to link theblocks 778 ₁, 778 ₂, . . . 778 _(N) may be any of a number of keyed orun-keyed Hash functions. In one embodiment, the blocks 778 ₁, 778 ₂, . .. 778 _(N) are subject to a hash function which produces n-bitalphanumeric outputs (where n is 256 or another number) from inputs thatare based on information in the blocks. Examples of such a hash functioninclude, but are not limited to, a SHA-type (SHA stands for Secured HashAlgorithm) algorithm, Merkle-Damgard algorithm, HAIFA algorithm,Merkle-tree algorithm, nonce-based algorithm, and anon-collision-resistant PRF algorithm. In another embodiment, the blocks778 ₁, 778 ₂, . . . , 778 _(N) may be cryptographically linked by afunction that is different from a hash function. For purposes ofillustration, the following description is made with reference to a hashfunction, e.g., SHA-2.

Each of the blocks 778 ₁, 778 ₂, . . . , 778 _(N) in the blockchainincludes a header, a version of the file, and a value. The header andthe value are different for each block as a result of hashing in theblockchain. In one embodiment, the value may be included in the header.As described in greater detail below, the version of the file may be theoriginal file or a different version of the original file.

The first block 778 ₁ in the blockchain is referred to as the genesisblock and includes the header 772 ₁, original file 774 ₁, and an initialvalue 776 ₁. The hashing scheme used for the genesis block, and indeedin all subsequent blocks, may vary. For example, all the information inthe first block 778 ₁ may be hashed together and at one time, or each ora portion of the information in the first block 778 ₁ may be separatelyhashed and then a hash of the separately hashed portions may beperformed.

The header 772 ₁ may include one or more initial parameters, which, forexample, may include a version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, duration, mediaformat, source, descriptive keywords, and/or other informationassociated with original file 774 ₁ and/or the blockchain. The header772 ₁ may be generated automatically (e.g., by blockchain networkmanaging software) or manually by a blockchain participant. Unlike theheader in other blocks 778 ₂ to 778 _(N) in the blockchain, the header772 ₁ in the genesis block does not reference a previous block, simplybecause there is no previous block.

The original file 774 ₁ in the genesis block may be, for example, dataas captured by a device with or without processing prior to itsinclusion in the blockchain. The original file 774 ₁ is received throughthe interface of the system from the device, media source, or node. Theoriginal file 774 ₁ is associated with metadata, which, for example, maybe generated by a user, the device, and/or the system processor, eithermanually or automatically. The metadata may be included in the firstblock 778 ₁ in association with the original file 774 ₁.

The value 776 ₁ in the genesis block is an initial value generated basedon one or more unique attributes of the original file 774 ₁. In oneembodiment, the one or more unique attributes may include the hash valuefor the original file 774 ₁, metadata for the original file 774 ₁, andother information associated with the file. In one implementation, theinitial value 776 ₁ may be based on the following unique attributes:

-   -   1) SHA-2 computed hash value for the original file    -   2) originating device ID    -   3) starting timestamp for the original file    -   4) initial storage location of the original file    -   5) blockchain network member ID for software to currently        control the original file and associated metadata

The other blocks 778 ₂ to 778 _(N) in the blockchain also have headers,files, and values. However, unlike the first block 772 ₁, each of theheaders 772 ₂ to 772 _(N) in the other blocks includes the hash value ofan immediately preceding block. The hash value of the immediatelypreceding block may be just the hash of the header of the previous blockor may be the hash value of the entire previous block. By including thehash value of a preceding block in each of the remaining blocks, a tracecan be performed from the Nth block back to the genesis block (and theassociated original file) on a block-by-block basis, as indicated byarrows 780, to establish an auditable and immutable chain-of-custody.

Each of the header 772 ₂ to 772 _(N) in the other blocks may alsoinclude other information, e.g., version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, and/or otherparameters or information associated with the corresponding files and/orthe blockchain in general.

The files 774 ₂ to 774 _(N) in the other blocks may be equal to theoriginal file or may be a modified version of the original file in thegenesis block depending, for example, on the type of processingperformed. The type of processing performed may vary from block toblock. The processing may involve, for example, any modification of afile in a preceding block, such as redacting information or otherwisechanging the content of, taking information away from, or adding orappending information to the files.

Additionally, or alternatively, the processing may involve merelycopying the file from a preceding block, changing a storage location ofthe file, analyzing the file from one or more preceding blocks, movingthe file from one storage or memory location to another, or performingaction relative to the file of the blockchain and/or its associatedmetadata. Processing which involves analyzing a file may include, forexample, appending, including, or otherwise associating variousanalytics, statistics, or other information associated with the file.

The values in each of the other blocks 776 ₂ to 776 _(N) in the otherblocks are unique values and are all different as a result of theprocessing performed. For example, the value in any one blockcorresponds to an updated version of the value in the previous block.The update is reflected in the hash of the block to which the value isassigned. The values of the blocks therefore provide an indication ofwhat processing was performed in the blocks and also permit a tracingthrough the blockchain back to the original file. This tracking confirmsthe chain-of-custody of the file throughout the entire blockchain.

For example, consider the case where portions of the file in a previousblock are redacted, blocked out, or pixelated in order to protect theidentity of a person shown in the file. In this case, the blockincluding the redacted file will include metadata associated with theredacted file, e.g., how the redaction was performed, who performed theredaction, timestamps where the redaction(s) occurred, etc. The metadatamay be hashed to form the value. Because the metadata for the block isdifferent from the information that was hashed to form the value in theprevious block, the values are different from one another and may berecovered when decrypted.

In one embodiment, the value of a previous block may be updated (e.g., anew hash value computed) to form the value of a current block when anyone or more of the following occurs. The new hash value may be computedby hashing all or a portion of the information noted below, in thisexample embodiment.

-   -   a) new SHA-2 computed hash value if the file has been processed        in any way (e.g., if the file was redacted, copied, altered,        accessed, or some other action was taken)    -   b) new storage location for the file    -   c) new metadata identified associated with the file    -   d) transfer of access or control of the file from one blockchain        participant to another blockchain participant

FIG. 7D illustrates an embodiment of a block which may represent thestructure of the blocks in the blockchain 790 in accordance with oneembodiment. The block, Block_(i), includes a header 772 ₁, a file 774 ₁,and a value 776 ₁.

The header 772 ₁ includes a hash value of a previous block Block_(i-1)and additional reference information, which, for example, may be any ofthe types of information (e.g., header information including references,characteristics, parameters, etc.) discussed herein. All blocksreference the hash of a previous block except, of course, the genesisblock. The hash value of the previous block may be just a hash of theheader in the previous block or a hash of all or a portion of theinformation in the previous block, including the file and metadata.

The file 774 ₁ includes a plurality of data, such as Data 1, Data 2, . .. , Data N in sequence. The data are tagged with Metadata 1, Metadata 2,. . . , Metadata N which describe the content and/or characteristicsassociated with the data. For example, the metadata for each data mayinclude information to indicate a timestamp for the data, process thedata, keywords indicating the persons or other content depicted in thedata, and/or other features that may be helpful to establish thevalidity and content of the file as a whole, and particularly its use adigital evidence, for example, as described in connection with anembodiment discussed below. In addition to the metadata, each data maybe tagged with reference REF₁, REF₂, . . . , REF_(N) to a previous datato prevent tampering, gaps in the file, and sequential reference throughthe file.

Once the metadata is assigned to the data (e.g., through a smartcontract), the metadata cannot be altered without the hash changing,which can easily be identified for invalidation. The metadata, thus,creates a data log of information that may be accessed for use byparticipants in the blockchain.

The value 776 _(i) is a hash value or other value computed based on anyof the types of information previously discussed. For example, for anygiven block Block_(i), the value for that block may be updated toreflect the processing that was performed for that block, e.g., new hashvalue, new storage location, new metadata for the associated file,transfer of control or access, identifier, or other action orinformation to be added. Although the value in each block is shown to beseparate from the metadata for the data of the file and header, thevalue may be based, in part or whole, on this metadata in anotherembodiment.

Once the blockchain 770 is formed, at any point in time, the immutablechain-of-custody for the file may be obtained by querying the blockchainfor the transaction history of the values across the blocks. This query,or tracking procedure, may begin with decrypting the value of the blockthat is most currently included (e.g., the last (N^(th)) block), andthen continuing to decrypt the value of the other blocks until thegenesis block is reached and the original file is recovered. Thedecryption may involve decrypting the headers and files and associatedmetadata at each block, as well.

Decryption is performed based on the type of encryption that took placein each block. This may involve the use of private keys, public keys, ora public key-private key pair. For example, when asymmetric encryptionis used, blockchain participants or a processor in the network maygenerate a public key and private key pair using a predeterminedalgorithm. The public key and private key are associated with each otherthrough some mathematical relationship. The public key may bedistributed publicly to serve as an address to receive messages fromother users, e.g., an IP address or home address. The private key iskept secret and used to digitally sign messages sent to other blockchainparticipants. The signature is included in the message so that therecipient can verify using the public key of the sender. This way, therecipient can be sure that only the sender could have sent this message.

Generating a key pair may be analogous to creating an account on theblockchain, but without having to actually register anywhere. Also,every transaction that is executed on the blockchain is digitally signedby the sender using their private key. This signature ensures that onlythe owner of the account can track and process (if within the scope ofpermission determined by a smart contract) the file of the blockchain.

FIGS. 8A and 8B illustrate additional examples of use cases forblockchain which may be incorporated and used herein. In particular,FIG. 8A illustrates an example 800 of a blockchain 810 which storesmachine learning (artificial intelligence) data. Machine learning relieson vast quantities of historical data (or training data) to buildpredictive models for accurate prediction on new data. Machine learningsoftware (e.g., neural networks, etc.) can often sift through millionsof records to unearth non-intuitive patterns.

In the example of FIG. 8A, a host platform 820 builds and deploys amachine learning model for predictive monitoring of assets 830. Here,the host platform 820 may be a cloud platform, an industrial server, aweb server, a personal computer, a user device, and the like. Assets 830can be any type of asset (e.g., machine or equipment, etc.) such as anaircraft, locomotive, turbine, medical machinery and equipment, oil andgas equipment, boats, ships, vehicles, and the like. As another example,assets 830 may be non-tangible assets such as stocks, currency, digitalcoins, insurance, or the like.

The blockchain 810 can be used to significantly improve both a trainingprocess 802 of the machine learning model and a predictive process 804based on a trained machine learning model. For example, in 802, ratherthan requiring a data scientist/engineer or other user to collect thedata, historical data may be stored by the assets 830 themselves (orthrough an intermediary, not shown) on the blockchain 810. This cansignificantly reduce the collection time needed by the host platform 820when performing predictive model training. For example, using smartcontracts, data can be directly and reliably transferred straight fromits place of origin to the blockchain 810. By using the blockchain 810to ensure the security and ownership of the collected data, smartcontracts may directly send the data from the assets to the individualsthat use the data for building a machine learning model. This allows forsharing of data among the assets 830.

The collected data may be stored in the blockchain 810 based on aconsensus mechanism. The consensus mechanism pulls in (permissionednodes) to ensure that the data being recorded is verified and accurate.The data recorded is time-stamped, cryptographically signed, andimmutable. It is therefore auditable, transparent, and secure. AddingIoT devices which write directly to the blockchain can, in certain cases(i.e., supply chain, healthcare, logistics, etc.), increase both thefrequency and accuracy of the data being recorded.

Furthermore, training of the machine learning model on the collecteddata may take rounds of refinement and testing by the host platform 820.Each round may be based on additional data or data that was notpreviously considered to help expand the knowledge of the machinelearning model. In 802, the different training and testing steps (andthe data associated therewith) may be stored on the blockchain 810 bythe host platform 820. Each refinement of the machine learning model(e.g., changes in variables, weights, etc.) may be stored on theblockchain 810. Furthermore, according to various embodiments, theauthenticator object which is stored on the blockchain 810 may be usedto reference data that was used to train the machine learning model.This provides verifiable proof of how the model was trained and whatdata was used to train the model. Furthermore, when the host platform820 has achieved a finally trained model, the resulting model may bestored on the blockchain 810.

After the model has been trained, it may be deployed to a liveenvironment where it can make predictions/decisions based on theexecution of the final trained machine learning model. For example, in804, the machine learning model may be used for condition-basedmaintenance (CBM) for an asset such as an aircraft, a wind turbine, ahealthcare machine, and the like. In this example, data fed back fromthe asset 830 may be input the machine learning model and used to makeevent predictions such as failure events, error codes, and the like.Determinations made by the execution of the machine learning model atthe host platform 820 may be stored on the blockchain 810 to provideauditable/verifiable proof. As one non-limiting example, the machinelearning model may predict a future breakdown/failure to a part of theasset 830 and create alert or a notification to replace the part. Thedata behind this decision may be stored by the host platform 820 on theblockchain 810. In one embodiment the features and/or the actionsdescribed and/or depicted herein can occur on or with respect to theblockchain 810.

New transactions for a blockchain can be gathered together into a newblock and added to an existing hash value. This is then encrypted tocreate a new hash for the new block. This is added to the next list oftransactions when they are encrypted, and so on. The result is a chainof blocks that each contain the hash values of all preceding blocks.Computers that store these blocks regularly compare their hash values toensure that they are all in agreement. Any computer that does not agree,discards the records that are causing the problem. This approach is goodfor ensuring tamper-resistance of the blockchain, but it is not perfect.

One way to game this system is for a dishonest user to change the listof transactions in their favor, but in a way that leaves the hashunchanged. This can be done by brute force, in other words by changing arecord, encrypting the result, and seeing whether the hash value is thesame. And if not, trying again and again and again until it finds a hashthat matches. The security of blockchains is based on the belief thatordinary computers can only perform this kind of brute force attack overtime scales that are entirely impractical, such as the age of theuniverse. By contrast, quantum computers are much faster (1000 s oftimes faster) and consequently pose a much greater threat.

FIG. 8B illustrates an example 850 of a quantum-secure blockchain 852which implements quantum key distribution (QKD) to protect against aquantum computing attack. In this example, blockchain users can verifyeach other's identities using QKD. This sends information using quantumparticles such as photons, which cannot be copied by an eavesdropperwithout destroying them. In this way, a sender and a receiver throughthe blockchain can be sure of each other's identity.

In the example of FIG. 8B, four users are present 854, 856, 858, and860. Each of pair of users may share a secret key 862 (i.e., a QKD)between themselves. Since there are four nodes in this example, sixpairs of nodes exists, and therefore six different secret keys 862 areused including QKD_(AB), QKD_(AC), QKD_(AD), QKD_(BC), QKD_(BD), andQKD_(CD). Each pair can create a QKD by sending information usingquantum particles such as photons, which cannot be copied by aneavesdropper without destroying them. In this way, a pair of users canbe sure of each other's identity.

The operation of the blockchain 852 is based on two procedures (i)creation of transactions, and (ii) construction of blocks that aggregatethe new transactions. New transactions may be created similar to atraditional blockchain network. Each transaction may contain informationabout a sender, a receiver, a time of creation, an amount (or value) tobe transferred, a list of reference transactions that justifies thesender has funds for the operation, and the like. This transactionrecord is then sent to all other nodes where it is entered into a poolof unconfirmed transactions. Here, two parties (i.e., a pair of usersfrom among 854-860) authenticate the transaction by providing theirshared secret key 862 (QKD). This quantum signature can be attached toevery transaction making it exceedingly difficult to tamper with. Eachnode checks their entries with respect to a local copy of the blockchain852 to verify that each transaction has sufficient funds. However, thetransactions are not yet confirmed.

Rather than perform a traditional mining process on the blocks, theblocks may be created in a decentralized manner using a broadcastprotocol. At a predetermined period of time (e.g., seconds, minutes,hours, etc.) the network may apply the broadcast protocol to anyunconfirmed transaction thereby to achieve a Byzantine agreement(consensus) regarding a correct version of the transaction. For example,each node may possess a private value (transaction data of thatparticular node). In a first round, nodes transmit their private valuesto each other. In subsequent rounds, nodes communicate the informationthey received in the previous round from other nodes. Here, honest nodesare able to create a complete set of transactions within a new block.This new block can be added to the blockchain 852. In one embodiment thefeatures and/or the actions described and/or depicted herein can occuron or with respect to the blockchain 852.

FIG. 9 illustrates an example system 900 that supports one or more ofthe example embodiments described and/or depicted herein. The system 900comprises a computer system/server 902, which is operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with computer system/server 902 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system/server 902 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 902 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 9, computer system/server 902 in cloud computing node900 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 902 may include, but are notlimited to, one or more processors or processing units 904, a systemmemory 906, and a bus that couples various system components includingsystem memory 906 to processor 904.

The bus represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 902 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 902, and it includes both volatileand non-volatile media, removable and non-removable media. System memory906, in one embodiment, implements the flow diagrams of the otherfigures. The system memory 906 can include computer system readablemedia in the form of volatile memory, such as random-access memory (RAM)910 and/or cache memory 912. Computer system/server 902 may furtherinclude other removable/non-removable, volatile/non-volatile computersystem storage media. By way of example only, storage system 914 can beprovided for reading from and writing to a non-removable, non-volatilemagnetic media (not shown and typically called a “hard drive”). Althoughnot shown, a magnetic disk drive for reading from and writing to aremovable, non-volatile magnetic disk (e.g., a “floppy disk”), and anoptical disk drive for reading from or writing to a removable,non-volatile optical disk such as a CD-ROM, DVD-ROM or other opticalmedia can be provided. In such instances, each can be connected to thebus by one or more data media interfaces. As will be further depictedand described below, memory 906 may include at least one program producthaving a set (e.g., at least one) of program modules that are configuredto carry out the functions of various embodiments of the application.

Program/utility 916, having a set (at least one) of program modules 918,may be stored in memory 906 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 918 generally carry out the functionsand/or methodologies of various embodiments of the application asdescribed herein.

As will be appreciated by one skilled in the art, aspects of the presentapplication may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present application may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present application may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Computer system/server 902 may also communicate with one or moreexternal devices 920 such as a keyboard, a pointing device, a display922, etc.; one or more devices that enable a user to interact withcomputer system/server 902; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 902 to communicate withone or more other computing devices. Such communication can occur viaI/O interfaces 924. Still yet, computer system/server 902 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 926. As depicted, network adapter 926communicates with the other components of computer system/server 902 viaa bus. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 902. Examples include, but are not limited to, microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Although an exemplary embodiment of at least one of a system, method,and non-transitory computer readable medium has been illustrated in theaccompanied drawings and described in the foregoing detaileddescription, it will be understood that the application is not limitedto the embodiments disclosed, but is capable of numerous rearrangements,modifications, and substitutions as set forth and defined by thefollowing claims. For example, the capabilities of the system of thevarious figures can be performed by one or more of the modules orcomponents described herein or in a distributed architecture and mayinclude a transmitter, receiver or pair of both. For example, all orpart of the functionality performed by the individual modules, may beperformed by one or more of these modules. Further, the functionalitydescribed herein may be performed at various times and in relation tovarious events, internal or external to the modules or components. Also,the information sent between various modules can be sent between themodules via at least one of: a data network, the Internet, a voicenetwork, an Internet Protocol network, a wireless device, a wired deviceand/or via plurality of protocols. Also, the messages sent or receivedby any of the modules may be sent or received directly and/or via one ormore of the other modules.

One skilled in the art will appreciate that a “system” could be embodiedas a personal computer, a server, a console, a personal digitalassistant (PDA), a cell phone, a tablet computing device, a smartphoneor any other suitable computing device, or combination of devices.Presenting the above-described functions as being performed by a“system” is not intended to limit the scope of the present applicationin any way but is intended to provide one example of many embodiments.Indeed, methods, systems and apparatuses disclosed herein may beimplemented in localized and distributed forms consistent with computingtechnology.

It should be noted that some of the system features described in thisspecification have been presented as modules, in order to moreparticularly emphasize their implementation independence. For example, amodule may be implemented as a hardware circuit comprising custom verylarge-scale integration (VLSI) circuits or gate arrays, off-the-shelfsemiconductors such as logic chips, transistors, or other discretecomponents. A module may also be implemented in programmable hardwaredevices such as field programmable gate arrays, programmable arraylogic, programmable logic devices, graphics processing units, or thelike.

A module may also be at least partially implemented in software forexecution by various types of processors. An identified unit ofexecutable code may, for instance, comprise one or more physical orlogical blocks of computer instructions that may, for instance, beorganized as an object, procedure, or function. Nevertheless, theexecutables of an identified module need not be physically locatedtogether but may comprise disparate instructions stored in differentlocations which, when joined logically together, comprise the module andachieve the stated purpose for the module. Further, modules may bestored on a computer-readable medium, which may be, for instance, a harddisk drive, flash device, random access memory (RAM), tape, or any othersuch medium used to store data.

Indeed, a module of executable code could be a single instruction, ormany instructions, and may even be distributed over several differentcode segments, among different programs, and across several memorydevices. Similarly, operational data may be identified and illustratedherein within modules and may be embodied in any suitable form andorganized within any suitable type of data structure. The operationaldata may be collected as a single data set or may be distributed overdifferent locations including over different storage devices, and mayexist, at least partially, merely as electronic signals on a system ornetwork.

It will be readily understood that the components of the application, asgenerally described and illustrated in the figures herein, may bearranged and designed in a wide variety of different configurations.Thus, the detailed description of the embodiments is not intended tolimit the scope of the application as claimed but is merelyrepresentative of selected embodiments of the application.

One having ordinary skill in the art will readily understand that theabove may be practiced with steps in a different order, and/or withhardware elements in configurations that are different than those whichare disclosed. Therefore, although the application has been describedbased upon these preferred embodiments, it would be apparent to those ofskill in the art that certain modifications, variations, and alternativeconstructions would be apparent.

While preferred embodiments of the present application have beendescribed, it is to be understood that the embodiments described areillustrative only and the scope of the application is to be definedsolely by the appended claims when considered with a full range ofequivalents and modifications (e.g., protocols, hardware devices,software platforms etc.) thereto.

What is claimed is:
 1. An apparatus comprising: a processor configuredto anonymize, via an anonymization service hosted within a trustedexecution environment (TEE), raw data provided by a computing node togenerate anonymized data, generate, via the anonymization service, anauthenticator object that binds together a hash of the raw data and ahash of the anonymized data, transmit the generated anonymized data tothe computing node, and submit the authenticator object to a blockchainledger via a blockchain transaction.
 2. The apparatus of claim 1,wherein the anonymization service is hosted within a secure enclave of ahardware processor of at least one of the computing node and a remotenode with respect to the computing node.
 3. The apparatus of claim 1,wherein the processor is configured to add a hash of the raw data to afirst field of the authenticator object, add a hash of the anonymizeddata to a second field of the authenticator object, and add acryptographic signature over the hash of the raw data and the hash ofthe anonymized data to a third field of the authenticator object.
 4. Theapparatus of claim 1, wherein the processor is further configured to adda digital certificate of the anonymization service to a fourth field ofthe authenticator object prior to submission of the authenticator objectto the blockchain ledger.
 5. The apparatus of claim 1, wherein theprocessor is further configured to receive, via an aggregator node, theanonymized data from the computing node, and query, via the aggregatornode, the blockchain ledger for the authenticator object that has beenstored to the blockchain ledger.
 6. The apparatus of claim 5, whereinthe processor is further configured to validate, via the aggregatornode, the anonymized data from the computing node based on theauthenticator object stored on the blockchain ledger, and transmit thevalidated anonymized data to a data processing pipeline.
 7. Theapparatus of claim 1, wherein the processor is configured to concatenatehash inputs used to create the hash of the raw data and the hash of theanonymized data, and sign the concatenated hash inputs with a digitalsignature of the anonymization service to create the cryptographicsignature.
 8. The apparatus of claim 1, wherein the processor is furtherconfigured to receive, via the anonymization service, a challengerequest from the computing node, and in response, transmit, via theanonymization service, cryptographic proof that the anonymizationservice is hosted in the TEE.
 9. A method comprising: anonymizing, viaan anonymization service hosted within a trusted execution environment(TEE), raw data provided by a computing node to generate anonymizeddata; generating, via the anonymization service, an authenticator objectthat binds together a hash of the raw data and a hash of the anonymizeddata; transmitting the generated anonymized data to the computing node;and submitting the authenticator object to a blockchain ledger via ablockchain transaction.
 10. The method of claim 9, wherein theanonymization service is hosted within a secure enclave of a hardwareprocessor of at least one of the computing node and a remote node withrespect to the computing node.
 11. The method of claim 9, wherein thegenerating comprises adding a hash of the raw data to a first field ofthe authenticator object, adding a hash of the anonymized data to asecond field of the authenticator object, and adding a cryptographicsignature over the hash of the raw data and the hash of the anonymizeddata to a third field of the authenticator object.
 12. The method ofclaim 9, wherein the method further comprises adding a digitalcertificate of the anonymization service to a fourth field of theauthenticator object prior to submitting the authenticator object to theblockchain ledger.
 13. The method of claim 9, wherein the method furthercomprises receiving, via an aggregator node, the anonymized data fromthe computing node, and querying, via the aggregator node, theblockchain ledger for the authenticator object that has been stored tothe blockchain ledger.
 14. The method of claim 13, wherein the methodfurther comprises validating, via the aggregator node, the anonymizeddata from the computing node based on the authenticator object stored onthe blockchain ledger, and transmitting the validated anonymized data toa data processing pipeline.
 15. The method of claim 9, wherein thegenerating comprises concatenating hash inputs used to create the hashof the raw data and the hash of the anonymized data, and signing theconcatenated hash inputs with a digital signature of the anonymizationservice to create the cryptographic signature.
 16. The method of claim9, wherein the method further comprises receiving, via the anonymizationservice, a challenge request from the computing node, and in response,transmitting, via the anonymization service, cryptographic proof thatthe anonymization service is hosted in the TEE.
 17. A non-transitorycomputer-readable medium comprising instructions which when executed bya processor cause a computer to perform a method comprising:anonymizing, via an anonymization service hosted within a trustedexecution environment (TEE), raw data provided by a computing node togenerate anonymized data; generating, via the anonymization service, anauthenticator object that binds together a hash of the raw data and ahash of the anonymized data; transmitting the generated anonymized datato the computing node; and submitting the authenticator object to ablockchain ledger via a blockchain transaction.
 18. The non-transitorycomputer-readable medium of claim 17, wherein the anonymization serviceis hosted within a secure enclave of a hardware processor of at leastone of the computing node and a remote node with respect to thecomputing node.
 19. The non-transitory computer-readable medium of claim17, wherein the method further comprises receiving, via an aggregatornode, the anonymized data from the computing node, and querying, via theaggregator node, the blockchain ledger for the authenticator object thathas been stored to the blockchain ledger.
 20. The non-transitorycomputer-readable medium of claim 17, wherein the method furthercomprises validating, via the aggregator node, the anonymized data fromthe computing node based on the authenticator object stored on theblockchain ledger, and transmitting the validated anonymized data to adata processing pipeline.